Articles avec mandats d'accès public - Kalyan VeeramachaneniEn savoir plus
Non disponibles : 2
Summary of evolutionary computation for wind farm layout optimization
DG Wilson, S Rodrigues, C Segura, I Loshchilov, F Hutter, GL Buenfil, ...
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2018
Exigences : UK Engineering and Physical Sciences Research Council
Markov Switching Copula Models for Longitudinal Data
A Cuesta-Infante, K Veeramachaneni
2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW …, 2016
Exigences : Government of Spain
Disponibles quelque part : 17
Modeling tabular data using conditional gan
L Xu, M Skoularidou, A Cuesta-Infante, K Veeramachaneni
Advances in neural information processing systems 32, 2019
Exigences : US National Science Foundation, Government of Spain
Tadgan: Time series anomaly detection using generative adversarial networks
A Geiger, D Liu, S Alnegheimish, A Cuesta-Infante, K Veeramachaneni
2020 ieee international conference on big data (big data), 33-43, 2020
Exigences : Government of Spain
ATM: A distributed, collaborative, scalable system for automated machine learning
T Swearingen, W Drevo, B Cyphers, A Cuesta-Infante, A Ross, ...
2017 IEEE international conference on big data (big data), 151-162, 2017
Exigences : US Department of Defense, Government of Spain
Autotuning algorithmic choice for input sensitivity
Y Ding, J Ansel, K Veeramachaneni, X Shen, UM O’Reilly, ...
ACM SIGPLAN Notices 50 (6), 379-390, 2015
Exigences : US Department of Energy
Evolutionary computation for wind farm layout optimization
D Wilson, S Rodrigues, C Segura, I Loshchilov, F Hutter, GL Buenfil, ...
Renewable energy 126, 681-691, 2018
Exigences : UK Engineering and Physical Sciences Research Council
The machine learning bazaar: Harnessing the ml ecosystem for effective system development
MJ Smith, C Sala, JM Kanter, K Veeramachaneni
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
Exigences : US Department of Defense
Learning vine copula models for synthetic data generation
Y Sun, A Cuesta-Infante, K Veeramachaneni
Proceedings of the aaai conference on artificial intelligence 33 (01), 5049-5057, 2019
Exigences : US National Science Foundation, Government of Spain
Sibyl: Understanding and addressing the usability challenges of machine learning in high-stakes decision making
A Zytek, D Liu, R Vaithianathan, K Veeramachaneni
IEEE Transactions on Visualization and Computer Graphics 28 (1), 1161-1171, 2021
Exigences : US National Science Foundation
Understanding user-bot interactions for small-scale automation in open-source development
D Liu, MJ Smith, K Veeramachaneni
Extended abstracts of the 2020 CHI conference on human factors in computing …, 2020
Exigences : US National Science Foundation
FeatureHub: Towards collaborative data science
MJ Smith, R Wedge, K Veeramachaneni
2017 IEEE International Conference on Data Science and Advanced Analytics …, 2017
Exigences : US National Science Foundation
An investigation of local patterns for estimation of distribution genetic programming
E Hemberg, K Veeramachaneni, J McDermott, C Berzan, UM O'Reilly
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
Exigences : Science Foundation Ireland
Cardea: An open automated machine learning framework for electronic health records
S Alnegheimish, N Alrashed, F Aleissa, S Althobaiti, D Liu, M Alsaleh, ...
2020 IEEE 7th International Conference on Data Science and Advanced …, 2020
Exigences : US National Science Foundation
Enabling collaborative data science development with the Ballet framework
MJ Smith, J Cito, K Lu, K Veeramachaneni
Proceedings of the ACM on Human-Computer Interaction 5 (CSCW2), 1-39, 2021
Exigences : US National Science Foundation
Sibyl: Explaining machine learning models for high-stakes decision making
A Zytek, D Liu, R Vaithianathan, K Veeramachaneni
Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing …, 2021
Exigences : US National Science Foundation
The Backfire Effects of Fairness Constraints
Y Sun, A Cuesta-Infante, K Veeramachaneni
Responsible Decision Making in Dynamic Environments. Baltimore, Maryland, 2022
Exigences : Government of Spain
Towards reducing biases in combining multiple experts online
Y Sun, I Ramirez, A Cuesta-Infante, K Veeramachaneni
arXiv preprint arXiv:1908.07009, 2019
Exigences : Government of Spain
In situ augmentation for defending against adversarial attacks on text classifiers
L Xu, L Berti-Equille, A Cuesta-Infante, K Veeramachaneni
International Conference on Neural Information Processing, 485-496, 2022
Exigences : Government of Spain
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